Moura has been the principal investigator of several Darpa, NSF,
ONR, and other Agencies grants, including the two multi University
Darpa research grants (DESA, Discovery and Exploitation of
Structure in Algorithms, started in May 2005, and OPAL,
Optimized Portable Algorithm Libraries) and of an NSF-ITR (medium
size) grant to develop SPIRAL.
SPIRAL is an interdisciplinary
project in the areas of signal processing, scientific computing,
compilers, computer architecture, machine learning, and mathematics,
see SPIRAL in the ECE news and in CMU Corporate
news. SPIRAL has been
licensed by SPIRALGEN, a
start-up company cofunded by Moura and four collaborators. SPIRALGEN further develops and
commercializes the distribution of SPIRAL. In August 2012, SPIRAL received a grant from the
DARPA
HACMS Program and in September 2012 a grant from the DARPA
PERFECT Program, both co-led by ECE Professor Franz Franchetti.

It applies algebraic signal processing methods to derive
automatically fast SW and HW implementations of DSP algorithms. What
this means is that at the click of a button SPIRAL generates
automatically for the target machine say a C program for your friendly
FFT, DCT, discrete wavelet transform, or FIR filter, to name a few of
the possibilities. SPIRAL's claim is that this C program will run on
your computerin the ball park of or significantly
faster than any other existing C program. In the SPIRAL
project, we are also working on generating automatically other
types of implementations, e.g., netlists FPGA, for these transforms.
These are high quality with respect to other performance metrics (say,
area, or power consumption) that are more appropriate for HW
implementations. The work on SPIRAL is described in the invited paper
SPIRAL: Code Generation for DSP Transforms
(pdf),
included in the IEEE Proceedings, February 2005 Special Issue on Program
Generation, Optimization, and Platform Adaptation, read the
Editorial (pdf).

José M. F. Moura is the
Philip L. and Marsha DowdUniversity
Professor at Carnegie Mellon University, with the Electrical and
Computer Engineering and, by courtesy, the BioMedical Engineering. He
is a member of the US National Academy of
Engineers, a corresponding member of the Portugal Academy of Science, an
IEEE Fellow, and a
Fellow of the AAAS.
He holds a D. Sc. in Electrical Engineering and Computer Science,
M.Sc., and EE degrees all from MIT and an EE degree from Instituto
Superior Técnico (IST, Portugal). He was a visiting Professor at MIT
(2006-2007, 1999-2000, and 1984-86), a visiting scholar at USC (Summers
of 79-81), and was on the faculty of IST (Portugal). In the academic
year 2013-14, he will be a visiting Professor with New York University
and CUSP, the Center for Urban Science
& Progress, on sabbatical leave from CMU.

Moura received, in 2000, the IEEE Third Millennium
Medal for outstanding achievements and contributions, the 2003
IEEE Signal Processing Meritorious Service Award, in
2006 an IBM Faculty Award, the 2007 CIT
Outsanding Research Award (with Markus Püschel), and the 2008
Philip L. Dowd Fellowship Award for Contributions to Engineering
Education. In 2010, he was elected University
Professor at Carnegie Mellon University to recognize his
professional achievement as well as breadth of interest and competence
and which is conferred on faculty members with exceptional national or
international distinction.

Moura's research interests include Network Science, see his current
projects on Cognitive
Networks, Global
Behavior in Large Scale Systems, and on distributed
inference algorithms on graphs. Other research area of interest is
statistical theory of shape: Shapes provide
a rich set of clues on the identity and topological properties of an
object. In many imaging environments, the same object appears to have
different shapes due to such distortions as translation, rotation,
reflection, scaling, or shearing. Also, the correspondence between
pixels of different distorted images of the same object is usually
unknown. Our work looks at shape invariants and at the geometry of the
shape space addressing questions like 'how close are two shapes' or
'how do we morph one shape into another.'